Using planar sensors for pallet detection

ABSTRACT

Example implementations may relate to a mobile robotic device that is operable to detect pallets using a distance sensor. According to these implementations, the robotic device causes the distance sensor to scan a horizontal coverage plane in an environment of the robotic device. Then, the robotic device receives from the distance sensor, sensor data indicative of the horizontal coverage plane. The robotic device compares the sensor data to a pallet identification signature. Based on the comparison, the robotic device detects a pallet located in the environment. Further, based on the sensor data, the robotic device determines a location and an orientation of the detected pallet.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority to U.S. patent application Ser. No.15/268,984 filed on Sep. 19, 2016 and entitled “Using Planar Sensors forPallet Detection,” which is incorporated herein by reference as if fullyset forth in this description.

BACKGROUND

A warehouse may be used for storage of goods by a variety of differenttypes of commercial entities, including manufacturers, wholesalers, andtransport businesses. Example stored goods may include raw materials,parts or components, packing materials, and finished products. In somecases, the warehouse may be equipped with loading docks to allow goodsto be loaded onto and unloaded from delivery trucks or other types ofvehicles. The warehouse may also use rows of pallet racks to allow forstorages of pallets, flat transport structures that contain stacks ofboxes or other objects. Additionally, the warehouse may use machines orvehicles for lifting and moving goods or pallets of goods, such ascranes and forklifts. Human operators may be employed to operatemachines, vehicles, and other equipment. In some cases, one or more ofthe machines or vehicles may be robotic devices guided by computercontrol systems.

SUMMARY

According to an example implementation, a mobile robotic device mayinclude one or more distance sensors. Moreover, the mobile roboticdevice may be configured to cause the one or more distance sensors toscan an environment in which the robotic device is located to producesensor data. The sensor data may be indicative of a two-dimensional (2D)representation of the environment. Specifically, the sensor data mayindicate distances to detect surfaces of objects in the environment. Acontrol system of the robotic device may analyze the data in order todetect objects in the environment. In an embodiment, the control systemmay compare the data to pallet signatures in order to detect any palletsthat may be located in the environment. Using pallet signatures may helpthe control system precisely determine the location and orientation ofany detected pallet. As such, the control system may provide the roboticdevice with specific instructions in order for the robotic device toaccurately interact with or manipulate the pallet.

In one aspect, a method is provided. The method involves causing, by acontrol system, a distance sensor coupled to a robotic device to scan ahorizontal coverage plane in an environment of the robotic device. Themethod also involves receiving, by the control system from the distancesensor, first sensor data indicative of the horizontal coverage plane.The method additionally involves comparing, by the control system, thefirst sensor data to a pallet identification signature, where the palletidentification signature is indicative of two dimensions of a supportmember of a pallet type. The method further involves based on thecomparison, detecting, by the control system, a pallet located in theenvironment. The method yet further involves based on the first sensordata, determining, by the control system, a location and an orientationof the detected pallet.

In another aspect, a mobile robotic device is provided. The mobilerobotic device includes a distance sensor coupled to a robotic device,two tines, and a control system. The control system is operable to causethe distance sensor coupled to a robotic device to scan a horizontalcoverage plane in an environment of the robotic device. The controlsystem is also operable to receive from the distance sensor, firstsensor data indicative of the horizontal coverage plane. The controlsystem is additionally operable to compare the first sensor data to apallet identification signature, where each pallet identificationsignature is indicative of two dimensions of at least one support memberof a pallet type. The control system is further operable to, based onthe comparison, detect a pallet located in the environment. The controlsystem is yet further operable to, based on the first sensor data,determine a location and orientation of the detected pallet.

In yet another aspect, a non-transitory computer readable medium isprovided. The non-transitory computer readable medium has stored thereininstructions executable by one or more processors to cause a mobilerobotic device to perform functions. In particular, the functionsinvolve causing a distance sensor coupled to a robotic device to scan ahorizontal coverage plane in an environment of the robotic device.Additionally, the functions involve receiving from the distance sensor,first sensor data indicative of the horizontal coverage plane. Further,the functions involve comparing the first sensor data to a palletidentification signature, where the pallet identification signature isindicative of two dimensions of a support member of a pallet type.Further, the functions include based on the comparison, detecting apallet located in the environment. Yet further the functions includebased on the first sensor data, determining a location and anorientation of the detected pallet.

In yet another aspect, a system is provided. The system may includemeans for causing, by a control system, a distance sensor coupled to arobotic device to scan a horizontal coverage plane in an environment ofthe robotic device. The system may also include means for receiving, bythe control system from the distance sensor, first sensor dataindicative of the horizontal coverage plane. The system may additionallyinclude means for, comparing, by the control system, the first sensordata to a pallet identification signature, where each palletidentification signature is indicative of two dimensions of a supportmember of a pallet type. The system may further include means for basedon the comparison, detecting, by the control system, a pallet located inthe environment. The system may yet further include means for based onthe first sensor data, determining, by the control system, a locationand orientation of the detected pallet.

These as well as other aspects, advantages, and alternatives will becomeapparent to those of ordinary skill in the art by reading the followingdetailed description, with reference where appropriate to theaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A shows a robotic fleet, according to an example implementation.

FIG. 1B is a functional block diagram illustrating components of arobotic fleet, according to an example implementation.

FIG. 2A shows a robotic truck unloader, according to an exampleimplementation.

FIG. 2B shows an autonomous guided vehicle, according to an exampleimplementation.

FIG. 2C shows an autonomous fork truck, according to an exampleimplementation.

FIG. 3 shows components of a robotic device, according to an exampleimplementation.

FIG. 4 shows an autonomous fork truck near two pallets, according to anexemplary embodiment.

FIG. 5 is a flowchart that shows a method, according to an exampleimplementation.

FIG. 6A shows a top view of autonomous fork truck near a pallet,according to an example implementation.

FIG. 6B shows two-dimensional distance sensor data, according to anexample implementation.

FIG. 7A shows a top view of an autonomous fork truck lifting a pallet,according to an exemplary embodiment.

FIG. 7B shows additional two-dimensional distance sensor data, accordingto an example implementation.

DETAILED DESCRIPTION

Example methods and systems are described herein. It should beunderstood that the words “example,” “exemplary,” and “illustrative” areused herein to mean “serving as an example, instance, or illustration.”Any implementation or feature described herein as being an “example,”being “exemplary,” or being “illustrative” is not necessarily to beconstrued as preferred or advantageous over other implementations orfeatures. The example implementations described herein are not meant tobe limiting. It will be readily understood that the aspects of thepresent disclosure, as generally described herein, and illustrated inthe figures, can be arranged, substituted, combined, separated, anddesigned in a wide variety of different configurations, all of which areexplicitly contemplated herein.

I. OVERVIEW

Example implementations may relate to methods and systems for detectingpallets located in an environment by using one or more distance sensors,such as distance sensors configured to collect two-dimensional (2D)planar distance measurements. In particular, a mobile robotic devicesuch as a fork truck may be deployed in a warehouse in which pallets arestored. The fork truck may be deployed in the warehouse in order to movepallets that are located in the warehouse. However, in order to move apallet, the fork truck may first need to precisely locate the pallet inthe warehouse. Further, the fork truck may need to determine theorientation of the pallet in order to locate pallet tine pockets inwhich the fork truck may insert its tines to lift the pallet.

In practice, various methods may be used to determine the location of apallet. For example, the environment may be highly structuredenvironment in which the fork truck may have knowledge of the preciselocation of pallets in the warehouse. In such an environment, the forktruck may receive instructions to pick up a pallet that is stored in aspecific area that is known to the fork truck. In other examples, thefork truck may rely on three-dimensional (3D) sensors to generate athree-dimensional (3D) representation of the warehouse, and may use thegenerated 3D representation of the warehouse to attempt to locate apallet.

Such solutions, however, may have shortcomings that may make itdifficult to accurately determine a location and orientation of a palletin an environment. For instance, maintaining a highly structuredenvironment is logistically difficult, especially in a dynamicenvironment such as a warehouse. Further, it may be advantageous todeploy a fork truck in any worksite, including worksites that are nothighly structured, and have the robotic device locate and move pallets.Other solutions, such as 3D sensors, can be prohibitively expensive,which may make it difficult to implement such solutions in a largenumber of fork trucks.

In an example embodiment, a mobile robotic device may include one ormore planar distance sensors that can be used to detect pallets in anenvironment. The one or more planar distance sensors may outputtwo-dimensional sensor data that is indicative of a horizontal coverageplane in the environment. In particular, the mobile robotic devicetravelling within an environment may use the one or more distancesensors to collect horizontal distance measurements that specifyrespective distances between the sensor and various points on surfacesin the environment. A control system of the mobile robotic device mayuse the sensor data to detect a pallet in the environment.

More specifically, the control system of the mobile robotic device mayanalyze the sensor data, and then compare the sensor data to variouspallet identification signatures in order to detect sensor data that isindicative of a pallet in the environment. A pallet identificationsignature may be indicative of a two-dimensional representation of oneor more identifiable features of a pallet, such as a support member ofthe pallet. Accordingly, the control system may analyze the sensor datain order to detect patterns in the data that may correspond to thefeatures of the pallet. The control system may then compare the detectedpatterns to the various identification signatures in order to determinewhether the detected patterns correspond to a pallet. The palletidentification signature may also be indicative of a pallet type. Thus,by determining a signature that corresponds to the detected patterns inthe data, the control system may determine the pallet type of thedetected pallet. Given that a pallet type may have standard dimensionsand design, a control system may determine the dimensions and thelocation of the features in the detected pallet based on the pallettype.

Furthermore, as the sensor data is indicative of distances to points onobjects, the control system may precisely determine the location and/orthe orientation of the detected pallet based on the location of thedetected feature patterns in the environment. For example, the controlsystem may use the pattern location and the pallet type to determine asix degree-of-freedom (DOF) pose of the pallet. By precisely determiningthe location and orientation of the pallet, the control system maydetermine where to position the robotic device in order to manipulatethe detected pallet. Subsequently, the control system may operate therobotic device in order to position the robotic device at the determinedlocation in order to manipulate the pallet.

II. EXAMPLE WAREHOUSE ENVIRONMENT

Example implementations may involve a robotic fleet deployed within awarehouse environment. More specifically, a combination of fixed andmobile components may be deployed within the environment to facilitateautomated processing of boxes, packages, or other types of objects.Example systems may involve automated loading and/or unloading of boxesand/or other objects, such as into storage containers or to and fromdelivery vehicles. In some example implementations, boxes or objects maybe automatically organized and placed onto pallets. Within examples,automating the process of loading/unloading trucks and/or the process ofcreating pallets from objects for easier storage within a warehouseand/or for transport to and from the warehouse may provide a number ofindustrial and business advantages.

According to various implementations, automating the process of loadingand/or unloading delivery trucks at the warehouse and/or the process ofcreating pallets may include the deployment of one or more differenttypes of robotic devices to move objects or perform other functions. Insome implementations, some of the robotic devices can be made mobile bycoupling with a wheeled base, a holonomic base (e.g., a base that canmove in any direction), or rails on the ceiling, walls, or floors. Inadditional implementations, some of the robotic devices may be madefixed within the environment as well. For instance, robotic manipulatorscan be positioned on elevated bases at different chosen locations withina warehouse.

As used herein, the term “warehouse” may refer to any physicalenvironment in which boxes or objects may be manipulated, processed,and/or stored by robotic devices. In some examples, a warehouse may be asingle physical building or structure, which may additionally containcertain fixed components, such as pallet racks for storing pallets ofobjects. In other examples, some fixed components may be installed orotherwise positioned within the environment before or during objectprocessing. In additional examples, a warehouse may include multipleseparate physical structures, and/or may also include physical spacesthat are not covered by a physical structure as well.

Further, the term “boxes” may refer to any object or item that can beplaced onto a pallet or loaded onto or unloaded from a truck orcontainer. For example, in addition to rectangular solids, “boxes” canrefer to cans, drums, tires or any other “simple” shaped geometricitems. Additionally, “boxes” may refer to totes, bins, or other types ofcontainers which may contain one or more items for transport or storage.For instance, plastic storage totes, fiberglass trays, or steel bins maybe moved or otherwise manipulated by robots within a warehouse. Examplesherein may also be applied toward objects other than boxes as well, andtoward objects of various sizes and shapes. Additionally, “loading” and“unloading” can each be used to imply the other. For instance, if anexample describes a method for loading a truck, it is to be understoodthat substantially the same method can also be used for unloading thetruck as well. As used herein, “palletizing” refers to loading boxesonto a pallet and stacking or arranging the boxes in a way such that theboxes on the pallet can be stored or transported on the pallet. Inaddition, the terms “palletizing” and “depalletizing” can each be usedto imply the other.

Within examples, a heterogeneous warehouse robot fleet may be used for anumber of different applications. One possible application includesorder fulfillment (e.g., for individual customers), in which cases maybe opened and individual items from the cases may be put into packagingwithin boxes to fulfill individual orders. Another possible applicationincludes distribution (e.g., to stores or other warehouses), in whichmixed pallets may be constructed containing groups of different types ofproducts to ship to stores. A further possible application includescross-docking, which may involve transporting between shippingcontainers without storing anything (e.g., items may be moved from four40-foot trailers and loaded into three lighter tractor trailers, andcould also be palletized). Numerous other applications are alsopossible.

Referring now to the figures, FIG. 1A depicts a robotic fleet within awarehouse setting, according to an example implementation. Morespecifically, different types of robotic devices may form aheterogeneous robotic fleet 100 that may be controlled to collaborate toperform tasks related to the processing of items, objects, or boxeswithin a warehouse environment. Certain example types and numbers ofdifferent robotic devices are shown here for illustration purposes, butrobotic fleet 100 may employ more or fewer robotic devices, may omitcertain types shown here, and may also include other types of roboticdevices not explicitly shown. Additionally, a warehouse environment isshown here with certain types of fixed components and structures, butother types, numbers, and placements of fixed components and structuresmay be used in other examples as well.

One example type of robotic device shown within robotic fleet 100 is anautonomous guided vehicle (AGV) 112, which may be a relatively small,mobile device with wheels that may function to transport individualpackages, cases, or totes from one location to another within thewarehouse. Another example type of robotic device is an autonomous forktruck 114, a mobile device with a forklift that may be used to transportpallets of boxes and/or to lift pallets of boxes (e.g., to place thepallets onto a rack for storage). An additional example type of roboticdevice is a robotic truck loader/unloader 116, a mobile device with arobotic manipulator as well as other components such as sensors tofacilitate loading and/or unloading boxes onto and/or off of trucks orother vehicles. For instance, robotic truck unloader 116 may be used toload boxes onto delivery truck 118, which may be parked adjacent to thewarehouse. In some examples, movements of delivery truck 118 (e.g., todeliver packages to another warehouse) may also be coordinated withrobotic devices within the fleet.

Other types of mobile devices than those illustrated here may also beincluded as well or instead. In some examples, one or more roboticdevices may use different modes of transportation besides wheels on theground. For instance, one or more robotic devices may be airborne (e.g.,quadcopters), and may be used for tasks such as moving objects orcollecting sensor data of the environment.

In further examples, the robotic fleet 100 may also include variousfixed components that may be positioned within the warehouse. In someexamples, one or more fixed robotic devices may be used to move orotherwise process boxes. For instance, a pedestal robot 122 may includea robotic arm elevated on a pedestal that is fixed to the ground floorwithin the warehouse. The pedestal robot 122 may be controlled todistribute boxes between other robots and/or to stack and unstackpallets of boxes. For example, the pedestal robot 122 may pick up andmove boxes from nearby pallets 140 and distribute the boxes toindividual AGV's 112 for transportation to other locations within thewarehouse.

In additional examples, robotic fleet 100 may employ additional fixedcomponents positioned within a warehouse space. For instance, highdensity storage racks 124 may be used to store pallets and/or objectswithin the warehouse. The storage racks 124 may be designed andpositioned to facilitate interaction with one or more robotic deviceswithin the fleet, such as autonomous fork truck 114. In furtherexamples, certain ground space may be selected and used for storage ofpallets or boxes as well or instead. For instance, pallets 130 may bepositioned within the warehouse environment at chosen locations forcertain periods of time to allow the pallets to be picked up,distributed, or otherwise processed by one or more of the roboticdevices.

FIG. 1B is a functional block diagram illustrating components of arobotic warehouse fleet 100, according to an example implementation. Therobotic fleet 100 could include one or more of various mobilecomponents, such as AGV's 112, autonomous fork trucks 114, robotic truckloaders/unloaders 116, and delivery trucks 118. The robotic fleet 100may additionally include one or more fixed components positioned withina warehouse or other environment, such as pedestal robots 122, densitystorage containers 124, and battery exchange/charging stations 126. Infurther examples, different numbers and types of the componentsillustrated within FIG. 1B may be included within a fleet, certain typesmay be omitted, and additional functional and/or physical components maybe added to the examples illustrated by FIGS. 1A and 1B as well. Tocoordinate actions of separate components, a global control system 150,such as a remote, cloud-based server system, may communicate (e.g.,through wireless communication) with some or all of the systemcomponents and/or with separate local control systems of individualcomponents.

Within examples, certain of the fixed components 120 may be installedbefore deployment of the rest of the robotic fleet 100. In someexamples, one or more mobile robots may be brought in to map a spacebefore determining placement of certain fixed components 120, such asthe pedestal robots 122 or battery exchange stations 126. Once mapinformation is available, the system may determine (e.g., by runningsimulations) how to layout the fixed components within the spaceavailable. In certain cases, a layout may be chosen to minimize thenumber of fixed components needed and/or the amount of space used bythose components. The fixed components 120 and mobile components 110 maybe deployed in separate stages or all at once. In additional examples,certain of the mobile components 110 may only be brought in duringparticular time periods or to complete particular tasks.

In some examples, global control system 150 may include a centralplanning system that assigns tasks to different robotic devices withinfleet 100. The central planning system may employ various schedulingalgorithms to determine which devices will complete which tasks at whichtimes. For instance, an auction type system may be used in whichindividual robots bid on different tasks, and the central planningsystem may assign tasks to robots to minimize overall costs. Inadditional examples, the central planning system may optimize across oneor more different resources, such as time, space, or energy utilization.In further examples, a planning or scheduling system may alsoincorporate particular aspects of the geometry and physics of boxpicking, packing, or storing.

Planning control may also be distributed across individual systemcomponents. For example, global control system 150 may issueinstructions according to a global system plan, and individual systemcomponents may also operate according to separate local plans.Additionally, different levels of detail may be included within a globalplan, with other aspects left for individual robotic devices to planlocally. For instance, mobile robotic devices may be assigned targetdestinations by a global planner but the full routes to reach thosetarget destinations may be planned or modified locally.

In additional examples, a central planning system may be used inconjunction with local vision on individual robotic devices tocoordinate functions of robots within robotic fleet 100. For instance, acentral planning system may be used to get robots relatively close towhere they need to go. However, it may be difficult for the centralplanning system to command robots with millimeter precision, unless therobots are bolted to rails or other measured components are used toprecisely control robot positions. Local vision and planning forindividual robotic devices may therefore be used to allow for elasticitybetween different robotic devices. A general planner may be used to geta robot close to a target location, at which point local vision of therobot may take over. In some examples, most robotic functions may beposition-controlled to get the robots relatively close to targetlocations, and then vision and handshakes may be used when needed forlocal control.

In further examples, visual handshakes may enable two robots to identifyone another by AR tag or other characteristics, and to performcollaborative operations within fleet 100. In additional examples, items(e.g., packages to be shipped) may be provided with visual tags as wellor instead, which may be used by robotic devices to perform operationson the items using local vision control. In particular, the tags may beused to facilitate manipulation of the items by the robotic devices. Forinstance, one or more tags on particular locations on a pallet may beused to inform a fork lift where or how to lift up the pallet.

In additional examples, deployment and/or planning strategies for fixedand/or mobile components may be optimized over time. For instance, acloud-based server system may incorporate data and information fromindividual robots within the fleet and/or from external sources.Strategies may then be refined over time to enable the fleet to use lessspace, less time, less power, less electricity, or to optimize acrossother variables. In some examples, optimizations may span acrossmultiple warehouses, possibly including other warehouses with roboticfleets and/or traditional warehouses. For instance, global controlsystem 150 may incorporate information about delivery vehicles andtransit times between facilities into central planning.

In some examples, a central planning system may sometimes fail, such aswhen a robot gets stuck or when packages get dropped in a location andlost. Local robot vision may also therefore provide robustness byinserting redundancy to handle cases where the central planner fails.For instance, as an automatic pallet jack passes and identifies anobject, the pallet jack may send information up to a remote, cloud-basedserver system. Such information may be used to fix errors in centralplanning, help to localize robotic devices, or to identify lost objects.

In further examples, a central planning system may dynamically update amap of the physical environment containing robotic fleet 100 and objectsundergoing processing by the robotic devices. In some examples, the mapmay be continuously updated with information about dynamic objects(e.g., moving robots and packages moved by robots). In additionalexamples, a dynamic map could contain information on both the currentconfiguration or placement of components within a warehouse (or acrossmultiple warehouses) as well as information about what is anticipated inthe near term. For instance, the map could show current locations ofmoving robots and anticipated locations of the robots in the future,which may be used to coordinate activity between robots. The map couldalso show current locations of items undergoing processing as well asanticipated future locations of the items (e.g., where an item is nowand when the item is anticipated to be shipped out).

In additional examples, some or all of the robots may scan for labels onobjects at different points within the process. The scans may be used tolook for visual tags that may be applied to individual components orspecific items to facilitate finding or keeping track of components anditems. This scanning may yield a trail of items constantly moving aroundas the items are manipulated or transported by robots. A potentialbenefit is added transparency, both on the supplier side and theconsumer side. On the supplier side, information about current locationsof inventory may be used to avoid overstocking and/or to move items orpallets of items to different locations or warehouses to anticipatedemand. On the consumer side, the information about current locations ofparticular items may be used to determine when a particular package willbe delivered with improved accuracy.

In some examples, some or all of the mobile components 110 withinrobotic fleet 100 may periodically receive charged batteries from abattery exchange station 126 equipped with multiple battery chargers. Inparticular, the station 126 may replace a mobile robot's old batterieswith recharged batteries, which may prevent robots from having to sitand wait for batteries to charge. The battery exchange station 126 maybe equipped with a robotic manipulator such as a robotic arm. Therobotic manipulator may remove batteries from an individual mobile robotand attach the batteries to available battery chargers. The roboticmanipulator may then move charged batteries located at the station 126into the mobile robot to replace the removed batteries. For instance, anAGV 112 with a weak battery may be controlled to move over to batteryexchange station 126 where a robotic arm pulls a battery out from theAGV 112, puts the battery in a charger, and gives the AGV 112 a freshbattery.

In further examples, battery exchanges may be scheduled by a centralplanning system. For instance, individual mobile robots may beconfigured to monitor their battery charge status. The robots mayperiodically send information to the central planning system indicatingthe status of their batteries. This information may then be used by thecentral planning system to schedule battery replacements for individualrobots within the fleet when needed or convenient.

In some examples, a fleet 100 may contain a number of different types ofmobile components 110 that use different types of batteries. A batteryexchange station 126 may therefore be equipped with different types ofbattery chargers for different types of batteries and/or mobile robots.The battery exchange station 126 may also be equipped with a roboticmanipulator that can replace batteries for different types of robots. Insome examples, mobile robots may have battery containers containingmultiple batteries. For instance, an autonomous fork truck 114 such as apallet jack may have a steel bucket with 3 or 4 batteries. The roboticarm at the station 126 may be configured to lift out the entire bucketof batteries and attach individual batteries to battery chargers on ashelf at the station 126. The robotic arm may then find chargedbatteries to replace the old batteries, and move those batteries backinto the bucket before reinserting the bucket into the pallet jack.

In further examples, global control system 150 and/or a separate controlsystem of the battery exchange station 126 may also automate batterymanagement strategies. For instance, each battery may have a barcode orother identifying mark so that the system can identify individualbatteries. A control system of the battery exchange station 126 maycount how many times individual batteries have been recharged (e.g., todetermine when to change water or empty batteries completely). Thecontrol system may also keep track of which batteries have spent time inwhich robotic devices, how long the batteries took to recharge at thestation 126 in the past, and other relevant properties for efficientbattery management. This battery usage information may be used by thecontrol system to select batteries for the robotic manipulator to giveto particular mobile robots.

In additional examples, a battery exchange station 126 may also involvea human operator in some cases. For instance, the station 126 couldinclude a rig where people can safely perform manual battery changing ordeliver new batteries to the station for deployment into the fleet 100when necessary.

FIGS. 2A-2C illustrate several examples of robotic devices that may beincluded within a robotic warehouse fleet. Other robotic devices whichvary in form from those illustrated here as well as other types ofrobotic devices may also be included.

FIG. 2A illustrates a robotic truck unloader, according to an exampleimplementation. In some examples, a robotic truck unloader may includeone or more sensors, one or more computers, and one or more roboticarms. The sensors may scan an environment containing one or more objectsin order to capture visual data and/or three-dimensional (3D) depthinformation. Data from the scans may then be integrated into arepresentation of larger areas in order to provide digital environmentreconstruction. In additional examples, the reconstructed environmentmay then be used for identifying objects to pick up, determining pickpositions for objects, and/or planning collision-free trajectories forthe one or more robotic arms and/or a mobile base.

The robotic truck unloader 200 may include a robotic arm 202 with agripping component 204 for gripping objects within the environment. Therobotic arm 202 may use the gripping component 204 to pick up and placeboxes to load or unload trucks or other containers. The truck unloader200 may also include a moveable cart 212 with wheels 214 for locomotion.The wheels 214 are shown to be mecanum wheels, although other types ofwheels are possible as well. Additionally, a wrap around front conveyorbelt 210 may be included on the holonomic cart 212. In some examples,the wrap around front conveyer belt may allow the truck loader 200 tounload or load boxes from or to a truck container or pallet withouthaving to rotate gripper 204.

In further examples, a sensing system of robotic truck unloader 200 mayuse one or more sensors attached to a robotic arm 202, such as sensor206 and sensor 208, which may be two-dimensional (2D) sensors and/or 3Ddepth sensors that sense information about the environment as therobotic arm 202 moves. The sensing system may determine informationabout the environment that can be used by a control system (e.g., acomputer running motion planning software) to pick and move boxesefficiently. The control system could be located on the device or couldbe in remote communication with the device. In further examples, scansfrom one or more 2D or 3D sensors with fixed mounts on a mobile base,such as a front navigation sensor 216 and a rear navigation sensor 218,and one or more sensors mounted on a robotic arm, such as sensor 206 andsensor 208, may be integrated to build up a digital model of theenvironment, including the sides, floor, ceiling, and/or front wall of atruck or other container. Using this information, the control system maycause the mobile base to navigate into a position for unloading orloading.

In further examples, the robotic arm 202 may be equipped with a gripper204, such as a digital suction grid gripper. In such implementations,the gripper may include one or more suction valves that can be turned onor off either by remote sensing, or single point distance measurementand/or by detecting whether suction is achieved. In additional examples,the digital suction grid gripper may include an articulated extension.In some implementations, the potential to actuate suction grippers withrheological fluids or powders may enable extra gripping on objects withhigh curvatures.

The truck unloader 200 may additionally include a motor, which may be anelectric motor powered by electrical power, or may be powered by anumber of different energy sources, such as a gas-based fuel or solarpower. Additionally, the motor may be configured to receive power from apower supply. The power supply may provide power to various componentsof the robotic system and could represent, for example, a rechargeablelithium-ion or lead-acid battery. In an example implementation, one ormore banks of such batteries could be configured to provide electricalpower. Other power supply materials and types are also possible.

FIG. 2B shows an autonomous guided vehicle (AGV), according to anexample implementation. More specifically, AGV 240 may be a relativelysmall, mobile robotic device that is capable of transporting individualboxes or cases. The AGV 240 may include wheels 242 to allow forlocomotion within a warehouse environment. Additionally, a top surface244 of the AGV 240 may be used to places boxes or other objects fortransport. In some examples, the top surface 244 may include rotatingconveyors to move objects to or from the AGV 240. In additionalexamples, the AGV 240 may be powered by one or more batteries that canbe quickly recharged at a battery charging station and/or exchanged forfresh batteries at a battery exchange station. In further examples, theAGV 240 may additionally include other components not specificallyidentified here, such as sensors for navigation. AGVs with differentshapes and sizes also may be included within a robotic warehouse fleet,possibly depending on the types of packages handled by a warehouse.

FIG. 2C shows an autonomous fork truck, according to an exampleimplementation. More specifically, autonomous fork truck 260 may includea forklift 262 for lifting and/or moving pallets of boxes or otherlarger materials. In some examples, the forklift 262 may be elevated toreach different racks of a storage rack or other fixed storage structurewithin a warehouse. The autonomous fork truck 260 may additionallyinclude wheels 264 for locomotion to transport pallets within thewarehouse. In additional examples, the autonomous fork truck may includea motor and power supply as well as a sensing system, such as thosedescribed with respect to robotic truck unloader 200.

In further examples, a sensing system of the autonomous fork truck 260may use one or more sensors attached to the body of the fork truck 260,such as sensor 266, which may be two-dimensional (2D) sensor or 3D depthsensor that senses information about the environment as the roboticdevices moves in an environment. The sensing system may determineinformation about the environment that can be used by a control system(e.g., a computer running motion planning software) to pick and movepallets efficiently. The control system could be located on the deviceor could be in remote communication with the fork truck. In furtherexamples, scans from one or more 2D or 3D sensors with fixed mounts on amobile base may be integrated to build up a digital model of theenvironment, including the sides, floor, ceiling, and/or front wall of atruck or other container. Using this information, the control system maycause the fork truck to navigate into a position for lifting pallets.

III. EXAMPLE CONFIGURATION OF A ROBOTIC DEVICE

FIG. 3 next shows an example configuration of a robotic device 300.Robotic device 300 may be any device that has a computing ability andinteracts with its surroundings with an actuation capability. Forexample, the robotic device 300 may take the form of any one of theabove-described devices, such as of a robotic truck unloader 200, an AGV240, or an autonomous fork truck 260. In other examples, the roboticdevice 300 could take the form of a humanoid robot, a robotic arm, aquadruped robot, among others. Additionally, the robotic device 300 mayalso be referred to as a robotic system, a robotic manipulator, or arobot, among others.

The robotic device 300 is shown to include processor(s) 302, datastorage 304, program instructions 306, controller 308, sensor(s) 310(e.g., a distance sensor 318), power source(s) 312, actuator(s) 314, andmovable component(s) 316 (e.g., a leveler 320). Note that the roboticdevice 300 is shown for illustration purposes only and robotic device300 may include additional components and/or have one or more componentsremoved without departing from the scope of the disclosure. Further,note that the various components of robotic device 300 may be arrangedand connected in any manner.

Processor(s) 302 may be a general-purpose processor or a special purposeprocessor (e.g., digital signal processors, application specificintegrated circuits, etc.). The processor(s) 302 can be configured toexecute computer-readable program instructions 306 that are stored inthe data storage 304 and are executable to provide the functionality ofthe robotic device 300 described herein. For instance, the programinstructions 306 may be executable to provide functionality ofcontroller 308, where the controller 308 may be configured to instructan actuator 314 to cause movement of one or more movable component(s)316, among other operations.

The data storage 304 may include or take the form of one or morecomputer-readable storage media that can be read or accessed byprocessor(s) 302. The one or more computer-readable storage media caninclude volatile and/or non-volatile storage components, such asoptical, magnetic, organic or other memory or disc storage, which can beintegrated in whole or in part with processor(s) 302. In someimplementations, the data storage 304 can be implemented using a singlephysical device (e.g., one optical, magnetic, organic or other memory ordisc storage unit), while in other implementations, the data storage 304can be implemented using two or more physical devices. Further, inaddition to the computer-readable program instructions 306, the datastorage 304 may include additional data such as diagnostic data, amongother possibilities.

The robotic device 300 may include one or more sensor(s) 310 such asforce sensors, proximity sensors, load sensors, position sensors, touchsensors, depth sensors, ultrasonic range sensors, infrared sensors,Global Positioning System (GPS) receivers, sonar, optical sensors,biosensors, Radio Frequency identification (RFID) sensors, Near FieldCommunication (NFC) sensors, wireless sensors, compasses, smoke sensors,light sensors, radio sensors, microphones, speakers, radar, cameras(e.g., color cameras, grayscale cameras, and/or infrared cameras), depthsensors (e.g., Red Green Blue plus Depth (RGB-D), lasers, a lightdetection and ranging (LIDAR) device, a structured-light scanner, and/ora time-of-flight camera), a stereo camera, motion sensors (e.g.,gyroscope, accelerometer, inertial measurement unit (IMU), and/or footstep or wheel odometry), and/or range sensors (e.g., ultrasonic and/orinfrared), among others. The sensor(s) 310 may provide sensor data tothe processor(s) 302 to allow for appropriate interaction of the roboticdevice 300 with the environment. Additionally, the robotic device 300may also include one or more power source(s) 312 configured to supplypower to various components of the robotic device 300. Any type of powersource may be used such as, for example, a gasoline engine or a battery.

The robotic device 300 may also include one or more actuator(s) 314. Anactuator is a mechanism that may be used to introduce mechanical motion.In particular, an actuator may be configured to convert stored energyinto movement of one or more components. Various mechanisms may be usedto power an actuator. For instance, actuators may be powered bychemicals, compressed air, hydraulics, or electricity, among otherpossibilities. With this arrangement, actuator(s) 314 may cause movementof various movable component(s) 316 of the robotic device 300. Themoveable component(s) 316 may include appendages such as robotic arms,legs, and/or hands, among others. The moveable component(s) 316 may alsoinclude a movable base, wheels, and/or end effectors, among others.Further, when a robotic device 300 includes at least one end effector,such an end effector may be a tool and/or a gripper, among others.

In accordance with the present disclosure, the robotic device 300 mayalso include at least one distance sensor 318. In particular, thedistance sensor 318 may be used by the robotic device 300 to determinepresence of one or more objects in the environment, to determinerespective locations of one or more objects, and/or to respectivelyidentify one or more objects, among other possibilities. In this way,the distance sensor 318 may help the robotic device 300 navigate theenvironment, avoid obstacles, and/or identify objects to be manipulated,among others.

Generally, the distance sensor 318 may be configured to detect radiationreflected from at least one object in the environment. Also, thedistance sensor 318 may be configured to generate a signal thatcorresponds to the detected radiation and thus produces sensor dataindicative of the environment in which the robotic device 300 isoperating. The distance sensor 318 may then provide the sensor data tothe controller 308 of the robotic device 300. In practice, the sensordata may be in form of distance measurements each specifying a distancebetween the distance sensor and at least one point on a surface in theenvironment, among other possibilities. The controller 308 may send thesensor data to a computing device and the computing device may generate,based on the sensor data, a two-dimensional representation of theenvironment.

Moreover, the source of the detected reflected radiation may beemissions (e.g., electromagnetic radiation) emitted by an emitter of therobotic device 300. In particular, the emitter may emit emissions thatare reflected from objects in the environment and then detected by thedistance sensor 318 so as to gain data about the environment. In anexample arrangement, the emitter may be incorporated as part of a sensorsystem used for such detection, such as by being incorporated as part ofthe distance sensor 318 itself. With this arrangement, the distancesensor 318 could thus take the form of a light detection and ranging(LIDAR) sensor, a time-of-flight (ToF) laser sensor, ultrasonic sensor,stereoscopic sensor, visual depth-by-motion sensor, laser or LEDtriangulation sensing, among others. In other arrangements, however, theemitter may be physically separate from the distance sensor 318. Otherarrangements are possible as well.

In some cases, the distance sensor 318 may be a 2D horizontal planardistance sensor. In particular, a 2D distance sensor may be configuredto emit emissions that substantially travel along a 2D plane in physicalspace. Also, the 2D distance sensor may be arranged on the roboticdevice 300 so as to emit such emissions substantially parallel to aparticular plane. In an example, the distance sensor 318 may emit theemissions substantially parallel to a ground surface on which therobotic device 300 is travelling. In another example, the distancesensor 318 may be arranged on the robotic device 300 so as to emit theemissions substantially parallel to the tines of a fork truck. Moreover,the distance sensor 318 may be arranged on the robotic device 300 so asto receive reflected radiation along a substantially parallel planerelative to the ground surface or may be arranged on the robotic device300 so as to receive reflected radiation along a substantially parallelplane relative to the tines of a fork truck.

Further, the distance sensor 318 may be configured to rotate about avertical axis (i.e., an axis that passes from top to bottom through thedevice) when scanning an environment. In particular, the distance sensor318 may be configured to scan the environment around the vehicle byrotating about the axis continuously while emitting emissions anddetecting reflected emissions off of objects in the environment. In someexamples, the distance sensor 318 may be configured to rotate 360° aboutthe vertical axis. In other examples, the distance sensor 318 may beconfigured to rotate 270° degrees about the vertical axis.

Further, the distance sensor 318, based on the configuration andcapabilities of the sensor 318, may have a coverage area that it may beconfigured to scan. Specifically, the coverage area of a distance sensoris the area in the environment to which the emitter of the roboticdevice 300 directs emissions. The coverage area is relative to theposition of the distance sensor 318 at a given moment. Further, thecoverage area of the distance sensor 318 may depend on the angle ofrotation of the distance sensor 318 about the axis, and may also dependon the distance (from the sensor) from which the distance sensor 318 canreceive accurate reflected emissions. The coverage area of a distancesensor 318 may also be referred to as the field-of-view (FOV) of thesensor. For example, the distance sensor 318 may be configured to rotate270° around the axis, and therefore may have a 270° FOV around therobotic device 300. In some examples, one of the distance sensors 318may be mounted on a top surface of the robotic device 300, and may beconfigured to rotate 360° about the vertical axis, which provides therobotic device 300 with a 360° FOV of the environment around the roboticdevice 300. In the example of a 2D sensor where emissions are sent andreceived substantially along a horizontal plane, the coverage area ofthe 2D sensor may also be referred to as a horizontal coverage plane.

IV. EXAMPLE SYSTEM AND METHOD

FIG. 4 illustrates a robotic device 400 deployed in a worksite thatincludes pallets, according to an exemplary embodiment. The roboticdevice 400 may be a fork truck that includes two tines 402. Further, adistance sensor 404 may be coupled to the robotic device. As illustratedin FIG. 4, the distance sensor may be coupled to the robotic deviceabove the two tines. However, the distance sensor 404 may be coupled toother areas or components of the robotic device 400. For example, thedistance sensor 404 may be placed between the tines of the roboticdevice. In another example, the distance sensor 404 may be located on atop surface of the robotic device 400. In yet another example, more thanone distance sensor may be coupled to the robotic device 400. Forinstance, a distance sensor may be placed on each tine of the roboticdevice. Other configurations and number of distance sensors coupled to arobotic device are also possible.

In another example, the distance sensor 404 may be mounted on anadjustable mounting platform that is coupled to the robotic device 400.The adjustable mounting platform may be configured to spatially reorientthe distance sensor 404 relative to a particular plane. Morespecifically, the platform may be any mechanical feature that isdirectly or indirectly attached to a portion of the robotic device 400and is movable relative to that portion of the robotic device 400. Inpractice, the platform may take on any feasible form, may be composed ofany feasible material, and may be of any feasible size and shape.Moreover, the platform may be arranged in one of various ways so as tobe configured spatially reorient the distance sensor 404 relative to theparticular plane. In an example, the platform may be arranged tospatially reorient the distance sensor 404 relative to a plane that isparallel to the ground surface. In another example, the platform may bearranged to spatially reorient the distance sensor 404 relative to aplane that is parallel to the tines 402.

In some embodiments, the distance sensor 404 may be attached at a chosenpoint on the robotic device 400 in order to scan a particular area withrespect to the robotic device 400. For instance, a distance sensor 404may be used for object detection, and therefore may be placed on an areaof the robotic device where the sensors may scan the environment inorder to detect objects. In an example embodiment, one or more distancesensors 404 may be coupled to the robotic device 400 in order to atleast detect pallets that may be located in the environment. As such,one or more of the distance sensors 404 may be placed at a height atwhich the sensor may detect features of the pallet that are describedherein. In an implementation, one or more of the distance sensors 404may be mounted between the tines of the robotic truck.

As illustrated in FIG. 4, the worksite in which the robotic device 404is deployed may include pallets. The worksite may include pallets ofdifferent types and/or sizes. The pallets may also be manufactured fromdifferent materials (e.g., wood, plastic, etc.). The different pallettypes may include a two way entry pallet 406 and a four way entry pallet408. The two way entry pallet 406 may have two tines pockets on twoopposite sides of the pallet 406. FIG. 4 illustrates the two tinepockets 410 from one side of pallet 406. The robotic device 400 may usethe tines 402 to lift the pallet from either side that has the pockettines 410. On the other hand, the four way entry pallet 408 has two tinepockets on each side of the pallet 408. Such an arrangement allows thefork truck 400 to engage any side of the pallet 408 in order to lift thepallet 408.

Further, a pallet (of either type) may include a plurality of supportmembers that support the deckboards onto which boxes are placed. Thesupport members may be elongated support members that span up to alength of the pallet (i.e., the length of the top surface of thepallet). For example, a pallet may comprise three or more parallelstringers with one or more deckboards fixed across the three or morestringers. The pallet 406 is one example of such a pallet. The pallet406 includes a plurality of deckboards 414 fixed on three parallelstringers 412. The gaps between the parallel stringers may form the tinepockets 410 of the pallet 406. Stringers may be used to manufacture bothtwo way entry and four way entry pallets.

In another example, the support members of a pallet may be a pluralityof blocks each of which serve as an individual leg. Pallet 408 is anexample of such a pallet. The pallet 408 may include nine blocks (i.e.,legs) 416 onto which one or more deckboards are fixed (FIG. 4illustrates two sides and five legs of the pallet 408). The nine legsmay be evenly spaced in a three by three array. In such an arrangement,the pallet 408 may be identical on each side, and may include two pockettines on each side. Thus, the pallet 408 is a four way entry pallet.

FIG. 5 is a flowchart illustrating a method 500, according to an exampleimplementation. In particular, the method 500 may be implemented tolocate pallets in an environment of a robotic device, such as therobotic device 400 in FIG. 4.

Method 500 shown in FIG. 5 (and other processes and methods disclosedherein) presents a method that can be implemented within an arrangementinvolving, for example, the robotic device 300 shown in FIG. 3 (or moreparticularly by components or subsystems thereof, such as by a processorand a non-transitory computer-readable medium having instructions thatare executable to cause the device to perform functions describedherein). Additionally or alternatively, method 500 may be implementedwithin any other arrangements and systems.

Method 500 and other processes and methods disclosed herein may includeoperations, functions, or actions as illustrated by one or more ofblocks 502-510. Although the blocks are illustrated in sequential order,these blocks may also be performed in parallel, and/or in a differentorder than those described herein. Also, the various blocks may becombined into fewer blocks, divided into additional blocks, and/orremoved based upon the desired implementation.

In addition, for the method 500 and other processes and methodsdisclosed herein, the flowchart shows functionality and operation of onepossible implementation of present implementations. In this regard, eachblock may represent a module, a segment, or a portion of program code,which includes one or more instructions executable by a processor forimplementing specific logical functions or steps in the process. Theprogram code may be stored on any type of computer readable medium, forexample, such as a storage device including a disk or hard drive. Thecomputer readable medium may include non-transitory computer readablemedium, for example, such as computer-readable media that stores datafor short periods of time like register memory, processor cache andRandom Access Memory (RAM). The computer readable medium may alsoinclude non-transitory media, such as secondary or persistent long termstorage, like read only memory (ROM), optical or magnetic disks,compact-disc read only memory (CD-ROM), for example. The computerreadable media may also be any other volatile or non-volatile storagesystems. The computer readable medium may be considered a computerreadable storage medium, for example, or a tangible storage device. Inaddition, for the method 500 and other processes and methods disclosedherein, each block in FIG. 5 may represent circuitry that is wired toperform the specific logical functions in the process.

An implementation of the method 500 may be described with respect toFIG. 6A and FIG. 6B. FIG. 6A illustrates a robotic device 600 that mayinclude some or all of the components of the robotic device 300illustrated in FIG. 3. A controller of the robotic device 600 mayperform the steps of the method 500 as described below.

At block 502, the method 500 involves causing, by a control system, adistance sensor coupled to a robotic device to scan a horizontalcoverage plane in an environment of the robotic device.

FIG. 6A illustrates the robotic device 600 whose controller may beperforming the steps of method 500, according to an example embodiment.The robotic device 600 may be a fork truck 600 that is located in aworksite that includes pallets, such as a pallet 608. Further, the forktruck 600 may include a distance sensor 602 that may be mounted on therobotic device or may be mounted on an adjustable platform. In anembodiment, the distance sensor 602 may be mounted on an area of therobotic device 600 above the robotic device 600's tines 628A.Furthermore, in some embodiments, the distance sensor 602 can be an asingle sensor, an array of sensors, or a plurality of sensors.

In an embodiment, the fork truck 600 may be deployed in a worksite inorder to move pallets that are located in the worksite. Accordingly, thefork truck 600 may need to precisely locate the pallets in theenvironment in order to move the pallets. Specifically, the fork truckmay need to know the type of a pallet to be moved, the location and theorientation of the pallet, and the location of the features of thepallet (e.g., tine pockets) that may be used to move the pallet, amongother possible determinations.

In an embodiment, a coverage plane of the distance sensor 602 may be anarea within the dotted coverage plane 604. That is, the FOV of thedistance sensor 602 may be a two-dimensional horizontal FOV around therobotic device 600. As further illustrated in FIG. 6A, a pallet 608 maybe located within the coverage plane 604 of the robotic device 600. Thepallet 608 may be a two way pallet 608 that has pocket tines on twoopposite ends. Specifically, the pallet 608 may include three supportmembers 610A, 612A, and 614A. Each of the support members may be astringer that extends along the length of the pallet 608.

Referring back to FIG. 5, at block 504, the method 500 involvesreceiving, by the control system from the distance sensor, first sensordata indicative of the horizontal coverage plane. In the context of FIG.6A, the control system may receive sensor data, from the distance sensor602, that is indicative of the coverage plane 604. In an embodiment, andas explained above, the data that is received from the distance sensor602 may be indicative of a distance to one or more points that areindicative of objects located within the coverage plane.

FIG. 6B illustrates distance sensor data 606, according to an exemplaryembodiment. The distance sensor data 606 may be indicative of the datathat may be collected by the distance sensor 602 that is coupled to therobotic device 600 of FIG. 6A. As illustrated in FIG. 6B, the sensordata 606 may be represented in a two-dimensional graph of theenvironment. Specifically, the sensor data 606 may include a series ofdetected points in the environment that are plotted in thetwo-dimensional graph of the environment. As illustrated in FIG. 6B, thegraph may include a horizontal x-axis and a vertical y-axis. Each axisrepresents a distance along a particular direction (e.g., horizontal orvertical). In example, the units of distance along each axis may bemeters. Other units are also possible.

As further illustrated in FIG. 6B, the distance sensor 602 may belocated at the origin point in the graph. As such, each point that isrepresented in the graph is indicative of a distance (in a particulardirection) from the distance sensor 602. In some representations of thedistance sensor data 606, curve fitting may be used to find a line thatbest fits one or more adjacent points. Further, in this example, the FOVof the distance sensor 602 is a 270° horizontal FOV around the roboticdevice. Accordingly, as shown in FIG. 6B, the sensor data 606 includesdistance points located 270° around the robotic device.

Referring back to FIG. 5, at block 506, the method 500 involvescomparing, by the control system, the first sensor data to a palletidentification signature, wherein the pallet identification signature isindicative of at least two dimensions of a support member of a pallettype.

In reference to FIGS. 6A and 6B, the distance sensor 602 may positionedon the robotic device 600 such that the sensor data 606 that iscollected by the distance sensor 602 may be indicative of a feature of apallet (assuming that a pallet, such as the pallet 608, is located inthe coverage area 604 of the distance sensor 602). In an embodiment, thecontrol system may analyze the sensor data 606 in order to determinewhich of the detected points included in the sensor data 606 areindicative of a feature of a candidate pallet. And once the controlsystem has identified the detected points that are indicative of thecandidate pallet, the control system may compare a feature of thecandidate pallet to a pallet identification signature to determinewhether the candidate pallet corresponds to an actual pallet of aparticular type. The control system may then use a location of adetected point respective to the robotic device 600 to determine alocation and orientation of the pallet.

In an embodiment, a pallet support member may be a pallet feature thatmay be used to identify a pallet. That is, the control system couldidentify where a pallet may be located in an environment by identifyingdata points in the sensor data that may correspond to a support memberof the pallet. In particular, the control system may determine thatcertain detected points in the sensor data could be indicative of aparticular type of a pallet support member (e.g., blocks or stringers),and may then designate those detected points as points that areindicative of a candidate support member of a candidate pallet (i.e.,the detected points are possibly indicative of a pallet support member).

Accordingly, in the example illustrated in FIGS. 6A and 6B, the controlsystem may analyze the sensor data 606 in order to determine which ofthe detected points are indicative of a support member of the pallet608, and may designate the detected points as corresponding to acandidate support member. The control system may then determine whetherthe detected data points correspond to a pallet (and not to an objectthat has a similar shape or features to a support member of the pallet).In particular, the control system may determine whether the candidatesupport member corresponds to a support member of a pallet by comparingthe data indicative of the candidate support member to one or morepallet identification signatures.

In an embodiment, the control system may determine points in the sensordata 606 that are indicative of a candidate support member by analyzingthe sensor data 606 and detecting a pattern in the data that maypossibly be indicative of a pallet support member. In practice, arobotic device may be facing a pallet at a particular angle, andtherefore may not be able to detect all four corners of the supportmembers of the pallet. For example, as illustrated in FIG. 6A, thepallet support member 610 may have two front corners on one side of thepallet 608 and two back corners on the other side the pallet 608. Therobotic device 600, when located at the position in FIG. 6A with respectto the pallet 608, may receive sensor data indicative of only certaincorners of the pallet support members 610A, 612A, and 614A. Despitedetecting only certain corners of the pallet support members of thepallet 608, the control system may determine patterns in the sensor data606 that may be indicative of at least one of the pallet support members610A, 612A, and 614A.

In an embodiment, a pattern that may be indicative of a pallet supportmember may include (i) detected points indicative of at least onecorner, and (ii) one or more discontinuities in the detected points thatmay be indicative of one or more other corners. The sensor dataindicative of a corner may include a sequence of detected points thatare arranged in the shape of a substantially 90° corner. Alternatively,if the detected points in the sensor data 606 have been curve fitted,the pattern indicative of a corner may be a fitted curve that has asubstantially 90° change in slope. Accordingly, the control system maydetect the data that is indicative of a corner by detecting a curve inthe curve fitted data that has a 90° change in slope. Further, thecorner that is detected by the control system by detecting a sequence ofpoints that are arranged in the shape of a substantially 90° corner orby detecting a curve that has a 90° change in slope may be a corner thatis fully in the FOV of the one or more distance sensors 602.

In the example of FIGS. 6A and 6B, the control system may analyze thesensor data 606 in order to detect a curve that has a substantially 90°change in slope. Alternatively, the control system may analyze thesensor data 606 to detect a sequence of detected points that arearranged in the shape of a substantially 90° corner. As illustrated inFIG. 6B, the control system may determine that a sequence of detectedpoints 610B includes a plurality of points that are arranged in a shapeof a substantially 90° corner, and therefore may determine that thesequence of detected points 610B may be indicative of a first candidatesupport member. In an example, a detected point 616B may correspond to aportion (edge) of the corner of the first candidate support member.

Further, the control system may detect one or more discontinuities inthe sequence of detected points 610B. As explained above, the one ormore discontinuities may be indicative of an edge of a corner that oneor more distance sensors may not fully detect due to the positioning ofa robotic device with respect to a pallet. As the discontinuities may beindicative of other corners of the first candidate member that thesensor data did not fully capture, the control system may be able todetermine the dimensions of the first candidate support member based onthe location of the discontinuities (i.e., the location of the othercorners of the candidate support member).

In the example of FIGS. 6A and 6B, the control system may furtheranalyze the sequence of points 610B and may detect two discontinuitiesin the sequence of detected points. Specifically, the control system maydetect a discontinuity after detected points 624 and 622. Accordingly,the control system may determine that the two points 624 and 622 may beindicative of two corners that are not fully in the FOV of the one ormore sensors 602. As illustrated in FIG. 6B, the discontinuity after thedetected point 624 may indicate a second front corner of the firstcandidate support member. The discontinuity after the detected point 622may be indicative of a back corner of the first candidate supportmember. Based on the location of the first discontinuity 624, thecontrol system may determine a width of the first candidate supportmember, and based on the location of the second discontinuity 622, thecontrol system may determine a length of the first candidate supportmember.

In some examples, the control system may then further analyze the datain order to detect a second candidate support member that may beassociated with the first candidate support member (i.e., the first andthe second candidate support members are part support members of thesame candidate pallet). Similar to detecting the first candidate supportmember, the control system may detect one or more corners of a secondcandidate support member in order to determine the dimensions of thesecond candidate support member. The control system may furtherdetermine dimensions of the candidate pallet based on the dimensions ofthe first and second candidate support members. For example, bydetermining the distance between the first and the second candidatesupport members, the control system may determine tine pocket dimensionsof the candidate pallet. In the example of FIGS. 6A and 6B, the controlsystem may determine that the sequence of detected points 612B may beindicative of the second candidate support member. The control systemmay use the determined dimensions of the first candidate support memberand the second candidate support member to determine the dimensions ofthe candidate pallet.

Subsequently, the control system may compare the dimensions of the firstcandidate support member and/or the second candidate support member toone or more pallet identification signatures in order to determinewhether the one or more candidate support members represent one or moresupport members of a known pallet type. If the dimensions match, thecontrol system may determine that the first and the second candidatesupport members correspond to support members of a pallet of the pallettype. The control system may have access to a library of palletidentification signatures that may be stored locally on a computingdevice that runs the control system and/or may be stored in a databaseto which the computing device may have access (e.g., an onlinedatabase).

In an embodiment, a pallet signature may specify features of aparticular pallet type. For instance, a pallet identification signaturemay be indicative of the features of a two way pallet or a four waypallet. The pallet signature may further indicate the dimensions of thepallet type. For example, the pallet signature may indicate a height ofthe pallet, a length of the pallet, a number of legs of the pallet, awidth of the tine pockets of the pallet, a number of the tine pockets,etc. In some examples, the pallet identification signature may alsoidentify the dimensions of each support member of a particular pallettype. Other dimensions and features may be calculated from thedimensions included in the pallet identification signature. For example,the distance between two support members of a pallet type may becalculated based on the dimensions of the pallet and the dimensions ofthe support members.

In an embodiment, comparing, by the control system, the first sensordata to one or more pallet identification signatures may includecomparing the dimensions of one or more candidate support members to thedimensions of the support members specified by one or more palletidentification signatures.

Referring back to FIG. 5, at block 508, method 500 involves based on thecomparison, detecting, by the control system, a pallet located in theenvironment. If there is a match between the dimensions of the one ormore candidate support members and the dimensions of a pallet type of apallet identification signature, the control system may determine thatthe one or more candidate support members correspond to the supportmembers of a pallet located in the environment. For example, inreference to FIGS. 6A and 6B, the control system may compare thesequences of detected points representative of candidate support membersto one or more pallet identification signatures. The dimensions of thecandidate pallet indicated by the candidate support members may matchthe dimensions of a first pallet type. Accordingly, the control systemmay determine that the sequence of points 610A corresponds to the palletsupport member 610A, that the sequence of detected points 612Bcorresponds to the pallet support member 612A of the pallet 608, andthat a sequence of detected points 614B corresponds to the palletsupport member 614A. The control system may further determine that thedetected points 616B, 618B, and 620B may respectively correspond to thecorners 616A, 618A, and 620A of the pallet 608.

At block 510, method 500 involves based on the first sensor data,determining, by the control system, a location and an orientation of thedetected pallet. The control system may determine the location and theorientation of the detected pallet based on the location of the detectedcorners and discontinuities in the sensor data. Further, the controlsystem may use the determined pallet type to determine the location ofthe features of the pallet. For example, in reference to FIGS. 6A and6B, the control system may determine the location of the tine pockets ofthe pallet 608, based on the determined dimensions of the pallet 608and/or the determination that the pallet 608 is a two way pallet.

Once the control system has determined the location and orientation ofthe pallet 608, the control system may accurately determine where toposition the robotic device 600 in order for the robotic device 600 topick up the pallet 608 using tines 628A of the robotic device 600.

In some embodiments, the control system may also use the sensor 606 todetect objects in the environment other than the pallet 608. Forinstance, as illustrated in FIG. 6B, the sensor data may include twosets of points 628B that are parallel to one another. The control systemmay determine that the points 628B correspond to the tines 628A of therobotic device 600. The determination may be based on the location ofthe detected points 628B with respect to the one or more sensors 602.The determination may also be based on the shape that is outlined by thedetected points 628B. In some examples, the control system may haveaccess to identification signatures for objects other than pallets.Accordingly, the control system may determine that the points 628Bcorrespond to the tines 628A based on a comparison of the points 628B totine identification signatures. Note that the sensor data 606 includeddata points indicative of the tines 628A since, in this example, the oneor more sensors 602 are positioned above the tines 628A.

FIG. 7A illustrates a robotic device 700 that has inserted its tines 716into tine pockets of a pallet 702, according to an exemplary embodiment.In an embodiment, the control system of the robotic device 700 may use adistance sensor 704 of the robotic device 700 to determine thepositioning of the tines 716 with respect to the pallet 702. Asexplained above, the distance sensor 704 may be oriented such that acoverage plane 706 of the distance sensor 704 is parallel to the tines716.

FIG. 7B illustrates sensor data 708 received from the distance sensor704, according to an exemplary embodiment. In an embodiment, the controlsystem of the robotic device 700 may analyze the sensor data 708 inorder to determine the positioning of the tines 716 with respect to thepallet 702. Specifically, the control system may analyze the sensor data708 in order to determine a location of the pallet 702 in theenvironment, and may then determine the positioning of the tines 716with respect to the position of the pallet 702 in the environment. Asillustrated in FIG. 7A, the pallet 702 may include support members 710A,712A, and 714A.

In an embodiment, the control system may determine the location of thepallet 702 (with respect to the tines 716) by determining a location ofone or more of the pallet support members 710A, 712A, and 714A. Forexample, the control system may analyze the sensor data 708 in order todetect one more corners of one or more support members of the pallet702. Specifically, the control system may detect at least one cornerthat is facing the distance sensor 704. As explained above, the controlsystem may detect a corner of a support member by detecting a sequenceof points that are arranged in a shape of a substantially 90° corner.Further, the control system may detect a back corner of a support memberby detecting a discontinuity in the detected points.

As the approximate location of the pallet 702 is known to the controlsystem, the control system may determine to which support member each ofthe detected corners corresponds. Further, the control system may detecta back corner of one or more of the support members of the pallet 702.The control system may detect a back corner by detecting a discontinuityin the sequence of points that are indicative of a particular supportmember. Determining the back corner may allow the control system todetermine the dimensions of the pallet 702 based on the location of thefront corner and the back corner of one or more of the support members.

For example, the control system may detect that a sequence of detectedpoints in the sensor data 708 are indicative of the support member 710Aby detecting a corner near an approximate location of the pallet supportmember 710A. By detecting the corner, the control system may determinethe location of the front side of the support member 710A. The sequenceof points that is indicative of the support member 710A is depicted inFIG. 7B as sequence of points 710B. Similarly, the control system maydetect respective sequences of points that correspond to each of thesupport members 712A and 714A. The sequence of points 712B and 714Bcorrespond to the support members 712A and 714A respectively.

Based on the determined location of the one or more pallet supportmembers, the control system may determine the location of the pallet702. By accurately determining the location of the pallet 702, thecontrol system may determine whether the tines 716 are positionedproperly with respect to the pallet 702 in order to lift the pallet 702.If the control system determines that the tines 716 are not positionedproperly, the control system may determine an adjustment to thepositioning of the tines in order to position the tines in a properposition at which the robotic device may lift the pallet. The controlsystem may then cause the robotic device 700 to reposition such that thetines 716 are positioned at the adjusted positioning with respect to thepallet 702.

As explained above, a robotic device may include one or more distancesensors that can be used to detect objects (e.g. pallets) in the roboticdevice's environment. As also explained above, each of the one or moredistance sensors may be mounted on different areas of the roboticdevice, and may be mounted in different orientations.

In an embodiment, a distance sensor may be placed below tines of arobotic device. In another embodiment, a distance sensor may be placeddirectly onto each of the tines of the robotic device. In such anembodiment, the distance sensor may be placed on a part of the tineswhere the distance sensor may not be damaged when lifting a pallet. Inyet another embodiment, a distance sensor may be placed between thebetween the tines of the robotic device. In yet another embodiment, adistance sensor may be placed above the tines.

In some embodiments, the robotic device may include other types ofsensors in addition to a distance sensor. The additional sensors may be1D, 2D, or 3D sensors that may be used for pallet detection. Forexample, the robotic device may include a distance sensor and one ormore monocular cameras. The control system may use a combination ofsensor data from the distance sensor and sensor data from the monocularcameras to detect a pallet signature in the environment. The data of themonocular camera may be a 2D image of the environment. In an embodiment,the control system may use the distance sensor data to detect a palletsignature (using the method disclosed herein), and may use the monocularcamera as a backup confirmation sensor. The monocular camera may alsoinclude failsafe protection and image collection to help develop visualmodels of pallets.

The distance sensor and the monocular camera may be mounted on therobotic device within close proximity to one another. Further, thesensors may be oriented in a horizontal coplanar orientation.Alternatively, the sensors may be oriented in a vertical coplanarorientation.

In another embodiment, a pair of monocular cameras may be mounted on abackrest of a forklift of the robotic device. The pair of monocularcameras may be orientated such that the coverage areas of the camerascover a front edge of a pallet that may be located in front of therobotic device. The pair of monocular cameras may be used for palletdetection, but may also be used to detect if a pallet shifted duringtransit, to avoid collisions, and upon placement of a pallet, to verifythat there is nothing occupying the space where the pallet is to beplaced.

In another embodiment, the control system may cause the orientation ofthe sensors of the robotic device to change as the robotic device goesthrough different stages of moving a pallet. For example, the pair ofmonocular cameras may be orientated in towards a first direction towardsa height that corresponds to a height of a pallet. In such anorientation, the monocular cameras may provide the control system withsupplemental data that the control may use, in addition to the distancesensor data, to detect a pallet. Once the pallet has been picked up, theorientation of the monocular cameras may change to an orientation inwhich the cameras may be used for obstacle detection.

In another embodiment, a distance sensor, in addition to thehorizontally orientated distance sensor, may be mounted on the roboticdevice in a manner to provide a vertical scanning plane. Such avertically oriented distance sensor may be used to provide some measureof assurance that nothing is below the tines when they are lowering apallet. Additionally and/or alternatively, the vertically orientedsensor may also be used to look for clearance or obstructions at thetine tips.

In another embodiment, a 3D sensor may be mounted on the robotic device.For example, a 3D LIDAR sensor may be used in addition to the 2Ddistance sensors for pallet detection. In another example, astereoscopic sensor may be used in addition to the 2D distance sensorsfor pallet detection. In yet another embodiment, one or more sensors,such as proximity or ultrasonic sensors, may be placed within the tinesof the robotic device. Such sensors may be used to determine whether thetines have been properly inserted into the tine pockets of a pallet. Thesensors may also be used to provide data on the orientation of thepallet as the robotic device moves the pallet from one location toanother.

V. CONCLUSION

The present disclosure is not to be limited in terms of the particularimplementations described in this application, which are intended asillustrations of various aspects. Many modifications and variations canbe made without departing from its spirit and scope, as will be apparentto those skilled in the art. Functionally equivalent methods andapparatuses within the scope of the disclosure, in addition to thoseenumerated herein, will be apparent to those skilled in the art from theforegoing descriptions. Such modifications and variations are intendedto fall within the scope of the appended claims.

The above detailed description describes various features and functionsof the disclosed systems, devices, and methods with reference to theaccompanying figures. In the figures, similar symbols typically identifysimilar components, unless context dictates otherwise. The exampleimplementations described herein and in the figures are not meant to belimiting. Other implementations can be utilized, and other changes canbe made, without departing from the spirit or scope of the subjectmatter presented herein. It will be readily understood that the aspectsof the present disclosure, as generally described herein, andillustrated in the figures, can be arranged, substituted, combined,separated, and designed in a wide variety of different configurations,all of which are explicitly contemplated herein.

The particular arrangements shown in the figures should not be viewed aslimiting. It should be understood that other implementations can includemore or less of each element shown in a given figure. Further, some ofthe illustrated elements can be combined or omitted. Yet further, anexample implementation can include elements that are not illustrated inthe figures.

While various aspects and implementations have been disclosed herein,other aspects and implementations will be apparent to those skilled inthe art. The various aspects and implementations disclosed herein arefor purposes of illustration and are not intended to be limiting, withthe true scope being indicated by the following claims.

The invention claimed is:
 1. A computer-implemented method comprising:receiving first sensor data indicative of a horizontal coverage plane inan environment; detecting a pallet located in the environment byidentifying a first portion and a second portion of the first sensordata, wherein the first portion of the first sensor data is indicativeof a first pallet support member of the pallet, wherein the secondportion is indicative of a second pallet support member, whereinidentifying the first portion and the second portion of the first sensordata comprises comparing the first sensor data to a palletidentification signature, and wherein the pallet identificationsignature is indicative of two pallet support members of a pallet type;and based on the first sensor data, determining a location and anorientation of the pallet.
 2. The computer-implemented method of claim1, wherein identifying the first portion of the first sensor data thatis indicative of the first pallet support member comprises: comparingthe first sensor data to a pallet identification signature, wherein thepallet identification signature is indicative of a pallet support memberof a pallet type.
 3. The computer-implemented method of claim 1, whereinthe first sensor data comprises a plurality of points each indicative ofa position of a respective surface in the environment.
 4. Thecomputer-implemented method of claim 1, wherein the method furthercomprises: identifying a first corner pattern indicative of a firstcorner of the first pallet support member, wherein the first cornerpattern comprises a substantially 90 degree change in a slope of a firstset of points within the first portion of the first sensor data;identifying a first discontinuity and a second discontinuity in thefirst set of points, wherein the first discontinuity and the seconddiscontinuity are indicative of a second corner and a third corner ofthe first pallet support member respectively; and based on respectivelocations of the first, second, and third corners, determining a firstand second dimension of the first pallet support member.
 5. Thecomputer-implemented method of claim 1, wherein the method furthercomprises: determining that a distance between the first pallet supportmember and the second pallet support member corresponds to a palletpocket width; and based on determining that the distance corresponds tothe pallet pocket width, determining that the first pallet supportmember and the second pallet support member are support members of thedetected pallet.
 6. The method of claim 1, further comprising:determining the pallet type of the pallet based on the first sensordata, wherein the pallet type is indicative of: (i) a number of supportmembers of the pallet type, (ii) dimensions of the pallet type, and(iii) a number and location of tine openings of the pallet type.
 7. Themethod of claim 6, further comprising: based on the pallet type of thedetected pallet, determining (i) a location and orientation of eachsupport member of the detected pallet, and (ii) respective locations ofeach tine opening of the detected pallet.
 8. The method of claim 7,wherein determining the location and the orientation of the pallet isfurther based on the determined location and orientation of each supportmember of the detected pallet.
 9. The method of claim 1, furthercomprising: operating a robotic device to insert a tine into a tinepocket of the detected pallet; after inserting the tine, receivingsecond sensor data indicative of an area surrounding the tine; analyzingthe second sensor data to identify data indicative of a front corner ofthe detected pallet; analyzing the second sensor data to identify dataindicative of an inflection point, wherein the inflection point isindicative of a back corner of the pallet; and based on a location ofthe front corner and a location of the back corner of the pallet,determining a positioning of the tine with respect to the detectedpallet.
 10. The method of claim 9, the method further comprising: basedon the positioning of the tine with respect to the pallet, adjusting therobotic device to center the tine within the tine pocket.
 11. A forkliftrobotic device comprising: a control system operable to: receive sensordata indicative of a horizontal coverage plane in an environment inwhich the forklift robotic device is deployed; identify, in the sensordata, (i) first sensor data indicative of a first candidate corner of afirst candidate pallet support member, (ii) second sensor dataindicative of a second candidate corner of the first candidate palletsupport member, and (iii) third sensor data indicative of a thirdcandidate corner of the first candidate pallet support member; based ona location of the first candidate corner, the second candidate corner,and the third candidate corner, determine (i) a width of the firstcandidate pallet support member, and (ii) a length of the firstcandidate pallet support member; compare the length and width todimensions of a pallet support member indicated in a palletidentification signature; determine that the length and the widthcorrespond to the dimensions of the pallet support member indicated bythe pallet identification signature; and based on determining that thelength and the width correspond to the dimensions of the pallet supportmember indicated by the pallet identification signature, detect a palletlocated in the environment.
 12. The forklift robotic device of claim 11,wherein the sensor data comprises a plurality of points each indicativeof a position of a respective surface in the environment.
 13. Theforklift robotic device of claim 11, further comprising: a distancesensor configured to generate the sensor data.
 14. The forklift roboticdevice of claim 13, further comprising: a camera, wherein the distancesensor and the camera are oriented in one of a horizontal coplanarorientation and a vertical coplanar orientation.
 15. The forkliftrobotic device of claim 11, further comprising: a camera mounted on abackrest of the forklift robotic device, wherein the camera isorientated such that a coverage area of the camera covers at least frontedge of a pallet when the pallet is carried by tines of the forkliftrobotic device.
 16. The forklift robotic device of claim 15, wherein thecontrol system is further operable to: monitor the coverage area of thecamera in order to detect a movement of the pallet when the pallet iscarried by tines of the forklift robotic device.
 17. The forkliftrobotic device of claim 11, further comprising: one or more sensors,wherein an orientation of each of the one or more sensors is adjustable,wherein the one or more sensors are oriented in a first direction whenthe forklift robotic device is searching for the pallet, and wherein theone or more sensors are oriented in a second direction when the forkliftrobotic device is carrying the pallet.
 18. A non-transitory computerreadable medium having stored therein instructions executable by one ormore processors to perform functions comprising: receiving sensor dataindicative of a horizontal coverage plane in an environment; detecting apallet located in the environment by identifying a first portion of thesensor data, wherein the first portion of the first sensor data isindicative of a first pallet support member of the pallet; and based onthe sensor data, determining a pallet type of the pallet, wherein thepallet type is indicative of: (i) a number of support members of thepallet type, (ii) dimensions of the pallet type, and (iii) a number andlocation of tine openings of the pallet type.